False touch filtering for capacitance sensing systems

ABSTRACT

Apparatuses and methods of false touch filtering are described. One device includes a controller and a capacitance sensing array including multiple sense elements (e.g., intersections of TX and RX electrodes). The controller includes a capacitance sensing circuit coupled to the capacitance sensing array, and a filter circuit coupled to the output of the capacitance sensing circuit. The controller is configured to receive, from the capacitance sensing circuit, data representing capacitances of the sense elements, process the data to identify activated sense elements, and filter the data to remove false touch events based on a spatial relationship of activated sense elements.

RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.61/602,283, filed Feb. 23, 2012, the entire contents of which areincorporated by reference.

TECHNICAL FIELD

The present disclosure relates generally to capacitance sensing systems,and more particularly to noise filtering in such systems.

BACKGROUND

Capacitance sensing systems can sense electrical signals generated onelectrodes that reflect changes in capacitance. Such changes incapacitance can indicate a touch event (i.e., the proximity of an objectto particular electrodes). Electrical sense signals can be degraded bythe presence of noise.

Noise in capacitance sensing systems can be conceptualized as including“internal” noise and “external noise”. Internal noise can be noise thatcan affect an entire system at the same time. Thus, internal noise canappear on all electrodes at the same time. That is, internal noise canbe a “common” mode type noise with respect to the sensors (e.g.,electrodes) of a system. Sources of internal noise can include, but arenot limited to: sensor power supply noise (noise present on a powersupply provided to the capacitance sensing circuit) and sensor powergeneration noise (noise arising from power generating circuits, such ascharge pumps, that generate a higher magnitude voltage from a lowermagnitude voltage).

In touchscreen devices (i.e., devices having a display overlaid with acapacitance sensing network), a display can give rise to internal noise.As but a few examples, display noise sources can include, but are notlimited to: LCD VCOM noise (noise from a liquid crystal display thatdrives a segment common voltage between different values), LCD VCOMcoupled noise (noise from modulating a thin film transistor layer in anLCD device that can be coupled through a VCOM node), and display powersupply noise (like sensor power generation noise, but for power suppliedof the display).

Common mode type noise can be addressed by a common mode type filterthat filters out noise common to all electrodes in a sense phase.

External noise, unlike internal noise, can arise from charge coupled bya sensed object (e.g., finger or stylus), and thus can be local to atouch area. Consequently, external noise is typically not common to allelectrodes in a sense phase, but only to a sub-set of the electrodesproximate to a touch event.

Sources of external noise can include charger noise. Charger noise canarise from charger devices (e.g., battery chargers that plug into ACmains, or those that plug into automobile power supplies). Chargersoperating from AC mains can often include a “flyback” transform that cancreate an unstable device ground with respect to “true” ground (earthground). Consequently, if a user at earth ground touches a capacitancesense surface of a device while the device is connected to a charger,due to the varying device ground, a touch can inject charge at a touchlocation, creating a localized noise event.

Other sources of external noise can arise from various other electricalfields that can couple to a human body, including but not limited to ACmains (e.g., 50/60 Hz line voltage), fluorescent lighting, brushedmotors, arc welding, and cell phones or other radio frequency (RF) noisesources. Fields from these devices can be coupled to a human body, whichcan then be coupled to a capacitance sensing surface in a touch event.

FIG. 21 is a schematic diagram of model showing charger noise in aconventional mutual capacitance sensing device. A voltage source VTX canbe a transmit signal generated on a TX electrode, Rp1 can be aresistance of a TX electrode, Cp1 can be (self) capacitance between a TXelectrode and device ground (which can be a charger ground CGND), Cm canbe a mutual capacitance between a TX electrode and a receive (RX)electrode, Cp2 can be a self-capacitance of an RX electrode, Rp2 can bea resistance of a RX electrode. Rx can represent an impedance of acapacitance sensing circuit.

Cf can be a capacitance between a sense object 2100 (e.g., finger). Avoltage source VCh_Noise can represent noise arising from differencesbetween CGND and earth ground (EGND). Voltage source VCh_Noise can beconnected to a device ground by an equivalent capacitance Ceq.

As shown in FIG. 21, a sense current (Isense) can be generated inresponse to source VTX that can vary in response to changes in Cm.However, at the same time, a noise current (Inoise) can arise a touchevent, due to the operation of a charger. A noise current (Inoise) canbe additive and subtractive to an Isense signal, and can give rise toerroneous sense events (touch indicated when no touch occurs) and/orerroneous non-sense events (touch not detected).

FIG. 22 shows capacitance sense values (in this case counts)corresponding to non-touch and touch events in a conventional systemsubject to external noise. As shown, while a device is not touched (NOTOUCH) noise levels are relatively small. However, while a device istouched (TOUCH) noise levels at the touch location are considerablyhigher.

While capacitance sensing systems can include common mode typefiltering, such filtering typically does not address the adverse affectsof external noise, as such noise is not present on all electrodes, butrather localized to electrodes proximate a sense event.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example, and not oflimitation, in the figures of the accompanying drawings in which:

FIG. 1 is a flow diagram of a capacitance sensing operation according toan embodiment.

FIG. 2 is a flow diagram of a capacitance sensing operation according toanother embodiment.

FIG. 3 is a block schematic diagram of a capacitance sensing systemaccording to an embodiment.

FIG. 4 is a block schematic diagram of a capacitance sensing systemhaving charger detection according to an embodiment.

FIG. 5 is a block schematic diagram of a capacitance sensing systemhaving a display alarm according to an embodiment.

FIG. 6 is a block schematic diagram of a capacitance sensing systemaccording to another embodiment.

FIG. 7 is a schematic diagram of a noise listening circuit according toan embodiment.

FIGS. 8A and 8B are plan views of a noise listening configurations for amutual capacitance sense network according to embodiments.

FIGS. 9A and 9B are diagrams showing noise listening operationsaccording to an embodiment.

FIG. 10 is a flow diagram of a noise listening operation according to anembodiment.

FIG. 11 is a flow diagram of a noise listening scan initializationoperation according to an embodiment.

FIG. 12 is a flow diagram of a noise listening restore-to-normaloperation according to an embodiment.

FIG. 13 is a flow diagram of a noise detection operation according to anembodiment.

FIG. 14 is a timing diagram showing a noise detection operation that canprovide an alarm condition according to an embodiment.

FIG. 15 is a flow diagram of a local noise filtering operation accordingto an embodiment.

FIGS. 16A and 16B are plan views showing electrode selection for scalingin a filter operation according to an embodiment.

FIGS. 17A and 17B are flow diagrams of an adaptive jitter filter (AJF)according to an embodiment.

FIGS. 18A and 18B are flow diagrams of a weighting function that can beincluded in the AJF according to an embodiment.

FIG. 19 is a diagram showing an AJF operation another to an embodiment.

FIG. 20 is a flow diagram of a median filter that can be included inembodiments.

FIG. 21 is a schematic diagram showing charger noise in a conventionalmutual capacitance sensing device.

FIG. 22 shows capacitance sense values with external noise correspondingto non-touch and touch events in a conventional system.

FIG. 23 is a graph of detected noise and three noise thresholdsaccording to one embodiment.

FIG. 24 is a flow chart illustrating a method of noise suppressionaccording to one embodiment.

FIG. 25 is a flow chart illustrating a method of noise suppression withfrequency hoping and false touch filtering according to one embodiment.

FIG. 26 is a graph of a signal during a touch event with noise accordingto one embodiment.

FIG. 27 illustrates a false touch and an actual touch on common receivesense elements according to one embodiment.

FIG. 28 illustrates a three-by-three square Z magnitude calculation ofan actual touch, an actual touch at a corner of the sensor network, andan actual touch at an edge of the sense network according to oneembodiment.

FIG. 29 illustrates a three-by-three square Z magnitude calculation ofan actual touch, an actual touch at a corner of the sensor network, andan actual touch at an edge of the sense network using virtual sensorsaccording to one embodiment.

FIGS. 30A and 30B are flow charts illustrating a method of false touchfiltering according to one embodiment.

FIGS. 31A and 31B are flow chart illustrating a method of false touchfiltering according to another embodiment.

FIG. 32 is a flow chart illustrating a method of false touch filteringaccording to another embodiment.

DETAILED DESCRIPTION

In the following description, for purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present invention. It will be evident, however, toone skilled in the art that the present invention may be practicedwithout these specific details. In other instances, well-known circuits,structures, and techniques are not shown in detail, but rather in ablock diagram in order to avoid unnecessarily obscuring an understandingof this description.

Reference in the description to “one embodiment” or “an embodiment”means that a particular feature, structure, or characteristic describedin connection with the embodiment is included in at least one embodimentof the invention. The phrase “in one embodiment” located in variousplaces in this description does not necessarily refer to the sameembodiment.

Various embodiments will now be described that show capacitance sensingsystems and methods that listen for noise and alter filtering of sensedvalues according to a noise level. In particular embodiments, if noiselevels are below a certain threshold, indicating the absence of (or lowlevels of) external noise (i.e., noise localized to a touch area),sensed values can be filtered for common mode type noise. However, ifnoise levels are above the threshold, sensed valued can be filtered toaccount for external noise. In particular embodiments, filtering forlocalized noise can include a median filter.

In the embodiments below, like items are referred to by the samereference character but with the leading digit(s) corresponding to thefigure number.

FIG. 1 shows a flow diagram of a capacitance sensing system operation100 according to one embodiment. A system operation 100 can include alistening operation 102, a no local noise processing path 104, and alocal noise processing path 106. A listening operation 102 can monitor asense network 108 for noise. A sense network 108 can include multipleelectrodes for sensing a capacitance in a sensing area. In a particularembodiment, a sense network 108 can be a mutual capacitance sensingnetwork having transmit (TX) electrodes that can be driven with atransmit signal, and receive (RX) electrodes coupled to the TXelectrodes by a mutual capacitance.

In some embodiments, a listening operation 102 can use the sameelectrodes used for capacitance sensing (e.g., touch position detection)for noise detection. In a very particular embodiment, a listeningoperation 102 can monitor all RX electrodes for noise. In an alternateembodiment, a listening operation 102 can monitor all RX electrodes in anoise listening operation. In yet another embodiment, a listeningoperation 102 can monitor both TX and RX electrodes in a listeningoperation.

A listening operation 102 can compare detected noise to one or morethreshold values to make a determination on the presence of noise. Ifnoise is determined to be present (Noise), a local noise processing path106 can be followed. In contrast, if no noise is determined to bepresent (No Noise), a no local noise processing path 104 can befollowed.

Processing paths 104 and 106 show how sense signals derived from sensenetwork 108 can be acquired and filtered. A no local noise processingpath 104 can acquire sense values from a sense network 108 with astandard scan 110 and non-local filtering 112. A standard scan 110 cansample electrode values to generate sense values using a set number ofsample operations and/or a set duration. Non-local filtering 112 canprovide filtering that is not directed at local noise events, such asthose arising from external noise. In particular embodiments, non-localfiltering 112 can include common mode type filtering that filters fornoise common to all sense electrodes.

A local noise processing path 106 can address the adverse affects oflocal noise, like that arising from external noise. A local noiseprocessing path 106 can acquire sense values from a sense network 108with an extended scan 114 and local filtering 116. An extended scan 114can sample electrode values with a larger number of sample operationsand/or a longer duration than the standard scan 110. In addition, localfiltering 116 can provide filtering to remove local noise events, suchas those arising from external noise. In particular embodiments, localfiltering 116 can include median filtering.

In this way, in response to the detection of noise, a processing ofcapacitance sense signals can switch from a standard scan time andnon-local filtering to an increased scan time and local filtering.

FIG. 2 shows a flow diagram of a capacitance sensing system operation200 according to another embodiment. In one particular embodiment,system operation 200 can be one implementation of that shown in FIG. 1.In addition to items like those shown in FIG. 1, FIG. 2 further shows anoise alarm operation 218 and touch position calculation operation 220.

In the embodiment shown, a listening operation 202 can include listenerscanning 222, listener common mode filtering (CMF) 224, and noisedetection 226. Listener scanning 222 can include measuring signals onmultiple electrodes of sense network 208. Scanning (noise signalacquisition) times can be selected based on sense network and expectednoise source(s). A listener CMF 224 can filter for noise common to allelectrodes being scanned. Such filtering can enable external type noise(noise local to a subset of the scanned electrodes) to pass through fornoise detection 226.

Noise detection 226 can establish whether any detected noise exceeds oneor more thresholds. In the embodiment shown, if noise is below a firstthreshold, noise detection 226 can activate a “No Noise” indication. Ifnoise is above a first threshold, noise detection 226 can activate a“Noise” indication. If noise is above a second threshold, greater thanthe first threshold, noise detection 226 can activate a “High Noise”indication.

In the case of a “No Noise” indication, processing can proceed accordingto no local noise processing path 204. Such a processing path 204 canutilize a standard scanning 210, which in the particular embodimentshown can include 8 sub-conversions per electrode. A sub-conversion canbe an elementary signal conversion event, and can reflect demodulationand/or integration results for one or more full input signal periods.Such processing can further include a CMF filtering 212 of values sensedon multiple electrodes. Such values can then be subject to baseline anddifference calculations 228, which can determine and difference betweencurrent sense values and baseline values. A sufficiently largedifference can indicate a touch event.

In the case of a “Noise” indication, processing can proceed according tolocal noise processing path 206. Local noise processing 206 can increasesignal acquisition time with an extended scanning 214 that utilizes 16sub-conversion (i.e., doubles a scanning time versus the no noise case).A processing path 206 can further include non-CMF filtering 216 that canfilter for external noise events affecting a local set of electrodes. Inthe particular embodiment shown, non-CMF filtering 216 can includemedian filtering 216-0 and non-linear filtering 216-1. Resultingfiltered sense values can then be subject to baseline and differencecalculations 228, like that described for the no local noise processingpath 204.

In the case of a “High Noise” indication, processing can includeactivation of an alarm indication 218. An alarm indication 218 caninform a user and/or a system that noise levels are high enough toresult in erroneous capacitance sensing results. In a very particularembodiment, such a warning can be a visual warning on a displayassociated with the sense network 208 (e.g., a touchscreen display).However, warnings may include various other indication types, includingbut not limited to: a different type of visual alarm (e.g., LED), anaudio alarm, or a processor interrupt, to name just a few. In theembodiment of FIG. 2, in response to a “High Noise” indication,processing may also proceed according to local noise processing path206. However, in other embodiments, capacitance sense processing couldbe interrupted, or additional filtering or signal boosting could occur.

Operation 200 can also include touch position calculations 220. Suchactions can derive positions of touch events from sense values generatedby processing paths 204 and 206. Touch position values generated bycalculations 220 can be provided to a device application, or the like.

In this way, a listening circuit can include common mode filtering ofsense electrodes to listen for localized noise events, such as externalnoise from a device charger or the like. Sense signals can be filteredbased on sensed noise values and/or an alarm can be triggered if noiselevels exceed a high threshold value.

Referring now to FIG. 3, a capacitance sensing system according to anembodiment is shown in a block schematic diagram and designated by thegeneral reference character 300. A system 300 can include a sensenetwork 308, switch circuits 332, an analog-to-digital converter (ADC)334, a signal generator 336, and a controller 330. A sense network 308can be any suitable capacitance sense network, including a mutualcapacitance sensing network, as disclosed herein. A sense network 308can include multiple sensors (e.g., electrodes) for sensing changes incapacitance.

Switch circuits 332 can selectively enable signal paths, both input andoutput signal paths, between a sense network 308 and a controller 330.In the embodiment shown, switch circuits 332 can also enable a signalpath between a signal generator 336 and sense network 308.

An ADC 334 can convert analog signals received from sense network 308via switching circuits 308 into digital values. An ADC 334 can be anysuitable ADC, including but not limited to a successive approximation(SAR) ADC, integrating ADC, sigma-delta modulating ADC, and a “flash”(voltage ladder type) ADC, as but a few examples.

A signal generator 336 can generate a signal for inducing sense signalsfrom sense network 308. As but one example, a signal generator 336 canbe a periodic transmit (TX) signal applied to one or more transmitelectrodes in a mutual capacitance type sense network. A TX signal caninduce a response on corresponding RX signals, which can be sensed todetermine whether a touch event has occurred.

A controller 330 can control capacitance sensing operations in a system300. In the embodiment shown, a controller can include sense controlcircuits 338, filter circuits 311, position determination circuits 320,and noise listening circuits 302. In some embodiments, controller 330circuits (e.g., 338, 311, 320 and 302) can be implemented by a processorexecuting instructions. However, in other embodiments, all or a portionof such circuits can be implemented by custom logic and/or programmablelogic.

Sense control circuits 338 can generate signals for controllingacquisition of signals from sense network 308. In the embodiment shown,sense control circuits 338 can activate switch control signals SW_CTRLapplied to switching circuits 332. In a particular embodiment, mutualcapacitance sensing can be employed, and sense control circuits 338 cansequentially connect a TX signal from signal generator 336 to TXelectrodes within sense network 308. As each TX electrode is driven withthe TX signal, sense control circuits 338 can sequentially connect RXelectrodes to ADC 334 to generate digital sense values for each RXelectrode. It is understood that other embodiments can use differentsensing operations.

Noise listening circuits 302 can also control acquisition of signalsfrom sense network 308 by activating switch control signals SW_CTRL.However, noise listening circuit 302 can configure paths to sensenetwork 308 to enable the detection of local noise, as opposed to touchevents. In a particular embodiment, noise listening circuit 302 canisolate signal generator 336 from sense network 308. In addition,multiple groups of electrodes (e.g., RX, TX or both) can besimultaneously connected to ADC 334. Noise listener 302 can filter suchdigital values and then compare them to noise thresholds to determine anoise level. Such actions can include arriving at “No Noise”, “Noise”and optionally “High Noise” determinations as described for FIG. 2.

In response to a noise determination from noise listening circuit 302, acontroller 330 can alter capacitance sensing operations. In oneembodiment, if noise is detected, signal acquisition times can beincreased (e.g., sub-conversions increased) and filtering can be changed(e.g., median filtering instead of common mode filtering).

Filter circuits 311 can filter sense values generated during senseoperations and noise detection operations. In the embodiment shown,filter circuits 311 can enable one or more types of median filtering 316and one or more types of CMF 312. It is understood that filter circuitscan be digital circuits operating on digital values representing sensedcapacitance. In a particular embodiment, filter circuits 311 can includea processor creating sense value data arrays from values output from ADC334. These arrays of sense values can be manipulated according to one ormore selected filtering algorithm to create an output array of filteredsense values. A type of filtering employed by filter circuits 311 can beselected based on detected noise levels.

Position determination circuits 320 can take filtered sense values togenerate touch position values (or no detected touches) for use by otherprocesses, such as applications run by a device.

In this way, a capacitance sensing system can include listening circuitsfor detecting noise values and digital filters, selectable based on adetected noise level.

Referring now to FIG. 4, a capacitance sensing system according toanother embodiment is shown in a block schematic diagram and designatedby the general reference character 400. In the embodiment of FIG. 4, anoise listening operation can vary based on a system condition. In theparticular embodiment shown, noise listening can be enabled or disabledbased on the presence of a charger.

A system 400 can include sections like those of FIG. 3, and suchsections can have the same or equivalent structures as FIG. 3. FIG. 4differs from FIG. 3 in that it also shows a charger interface 440,battery interface 448, power control circuits 441, and application(s)446.

A charger interface 440 can enable power to be provided to system 400that charges a battery via a battery interface 448. In some embodiments,a charger interface 440 can be a physical interface that creates amechanical connection between a charger 442 and the system 400. In aparticular embodiment, such a physical connection can include a groundconnection that can give rise to injected current as represented in FIG.22. However, alternate embodiments can include wireless charginginterfaces.

Power control circuits 441 can activate a charging indication (Charging)when a charger 442 is coupled to a system 400, and thus can present anexternal noise source. In addition, power control circuits 441 cancontrol charging operations of a battery via batter interface 448.

Referring still to FIG. 4, listening circuits 402′ can vary listeningoperations in response to a charger indication (Charging). In oneembodiment, if the Charging indication is inactive, indicating that acharger 442 is not present, listening circuits 402′ can be disabled. Ifthe Charging indication is active, listening circuits 402′ can beenabled. However in other embodiments, listening circuits 402′ canswitch between different types of listening operations based on acharger indication (Charging).

It is understood that while a charger can be one source of noise, othertypes of power supplies for a device can be a source of noise (e.g.,AC/DC converters within such devices). For example, some devices can beconnected to a computer with its own external power supply, or even acharger within an automobile.

Application(s) 446 can be programs executable by a system 400 utilizingposition values from position determination circuits 420.

In this way, a capacitance sensing system can vary listening circuitoperations that detect noise values based on a physical condition of thesystem.

Referring now to FIG. 5, a capacitance sensing system according to afurther embodiment is shown in a block schematic diagram and designatedby the general reference character 500. In the embodiment of FIG. 5, analarm can be generated when noise exceeds a threshold value.

A system 500 can include sections like those of FIG. 3, and suchsections can have the same or equivalent structures as FIG. 3. FIG. 5differs from FIG. 3 in that is also shows an alarm circuit 518, adisplay 548 and application(s) 546.

A listening circuit 502 can provide a noise level indication to alarmcircuit 516 when detected noise is determined to exceed a highthreshold. An alarm circuit 516 can activate one or more alarms, whenthe noise threshold is exceeded. In the very particular embodimentshown, alarm circuit 516 can provide an alarm (Alarm-Display) to display548. In response to such an alarm, a display 548 can show a visual alarmindicating that touch inputs are affected by noise (e.g., touch inputswill not be accepted, etc.). In one particular embodiment, display 548and sense network 508 can be a touchscreen assembly (i.e., sense network508 is physically overlaid on display 548).

In some embodiments, an alarm circuit 516 can provide an alarm toapplication(s) 546. Such applications can then alter execution and/orgenerate their own alarm. Further, as noted in conjunction with FIG. 2,an alarm can take various other forms (e.g., an interrupt, or the like).

In this way, a capacitance sensing system can generate an alarm for auser in the event noise levels exceed a predetermined threshold.

Referring now to FIG. 6, a capacitance sensing system according toanother embodiment is shown in a block schematic diagram and designatedby the general reference character 600. The embodiment of FIG. 6 showsan implementation utilizing a processor and instructions to providelistening, selectable filtering, and alarm functions.

A system 600 can include switching circuits 632, controller 630, acapacitance sense system 678, oscillator circuits 650, an ADC 634,instruction memory 660, communication circuits 656, random access memory(RAM) 658, and a power control circuits 644.

Switching circuits 632 can provide analog signal paths between a sensenetwork 608 and circuits within a system 600. In the embodiment shown,switching circuits 632 can include a number of channels 664-0 to -7 anda channel multiplexer (MUX) 672. Switching and MUXing operations withinswitching circuits 632 can be controlled by switch control signals(SW_CTRL) provided by controller 630. Each channel (664-0 to -7) caninclude a number of input/output (I/O) switches (one shown 666)connected to an I/O connection 631, an I/O MUX 668, and a sample andhold (S/H) circuit 670. Each I/O switch (666) can connect acorresponding I/O 631 to a RX path (one shown as 674) or a TX path (oneshown as 676). I/O MUX 668 can connect one of RX paths 674 within achannel to the corresponding S/H circuit 670. TX paths 676 can receive aTX signal. A channel MUX 672 can selectively connect a S/H circuit 670within each channel (664-0 to -7) to ADC 634.

An ADC 634 can include any suitable ADC as described herein, or anequivalent.

FIG. 6 shows a system 600 connected to mutual capacitance sense network608. Sense network 608 can include TX electrodes formed by TX plates(one shown as 608-0) and RX plates (one shown as 608-1). By operation ofswitching circuits 632, TX electrodes can be connected to a TX path 676,while multiple RX electrodes are connected to corresponding RX paths674.

In the embodiment of FIG. 6, a controller 630 can include a processor630-0 and digital processing circuits 630-1. A processor 630-0 cancontrol operations of digital processing circuits 630-1 in response toinstructions stored in instruction memory 660. Instruction memory 660can include noise listening instructions 602, alarm control instructions618, and filter instructions 611. Filter instructions 611 can includemultiple filtering operations, and in the embodiment shown, can includemedian filter instructions 616 and CMF instructions 612.

In response to noise listening instructions 602, a controller 630 cangenerate signals that connect multiple I/Os 631 to ADC 634. In oneembodiment, values can be subject to an initial listening CMF operation.Such an operation can be called from filter instructions 611 or be builtinto noise listening instructions 602. Resulting values can then becompared to one or more thresholds to determine a noise level. If anoise level exceeds a certain level, a listening circuit 602 canestablish capacitance sensing parameters directed to filtering localnoise (e.g., an external noise source). In some embodiments, suchparameters can include those described for other embodiments, includingan increased scan time and/or non-common mode (e.g., median) filtering.In addition, if a noise threshold level is above another certain level,alarm instructions 618 can be called to generate an appropriate alarm.

Processor 630-0 alone, or in combination with digital processingcircuits 630-1, can perform arithmetic and logic operations fordetecting noise and/or filtering sense values.

Capacitance sensing system 678 can include circuits for performingcapacitance sensing operations. In some embodiments, capacitance sensingsystem 678 can include sense control circuits 638 that generate switchcontrol signals for controlling switching circuits 632. In oneembodiment, capacitance sensing system 678 can perform sensing operationbased on criteria established by controller 630. In a particularembodiment, a controller 630 can vary a sensing time (e.g., number ofsub-conversions) based on a noise level.

Referring still to FIG. 6, oscillator circuits 650 can generate signalsfor controlling timing of operations within system 600. In oneembodiment a TX signal presented at TX paths 676 can be provided by, orderived from signals generated by oscillator circuits 650.

Communication circuits 656 can provide capacitance sensing results toother systems or circuits of a device containing the capacitance sensingsystem 600. RAM 658 can be provided to enable processor 630-0 to executearithmetic operations and/or temporarily store instruction data. Inparticular embodiments, a RAM 658 can store sense value matrices thatare manipulated by processor 630-0 to detect noise and/or filtercapacitance sense values.

Power control circuits 644 can generate power supply voltages forvarious portions within a system 600. In some embodiments, power controlcircuits 644 provide a charging indication, like that described for FIG.4, which can indicate when a charger is coupled to the system 600. Aprocessor 630-0 can then bypass noise listening instructions 602 in theabsence of a charger, or may select between multiple listeningalgorithms based on the presence or absence of a charger.

FIG. 6 also shows timer circuits 652 and programmable circuits 654.Timer circuits 652 can provide timing functions for use by varioussections of system 600. Programmable circuits 654 can be programmed withconfiguration data to perform custom function. In the embodiment shown,programmable circuits 654 can include programmable digital blocks.

In a very particular embodiment, a system 600 can be implemented withthe PSoC® 3 type programmable system-on-chip developed by CypressSemiconductor Corporation of San Jose, Calif. U.S.A.

In this way, a capacitance sensing system can include a processor thatcan execute any of: noise listening instructions, noise alarminstructions, median filtering, and CMF.

FIG. 7 is a schematic diagram showing a noise listening configurationfor a mutual capacitance sense network 708 according to an embodiment. Asense network 708 can include first electrodes (one shown as 780) andsecond electrodes (one shown as 782) coupled to one another by a mutualcapacitance Cm. Noise, represented by noise voltage source 784, on oneor more first electrodes 780 can induce a noise signal (Ix) by mutualcapacitance coupling. In a very particular embodiment, first electrodes780 can be TX electrodes and second electrodes 782 can be RX electrodes.However, the TX electrodes are not driven by any system generated TXsignal, but rather are used to detect noise.

FIGS. 8A and 8B show different noise listening configurations accordingto embodiments.

FIG. 8A shows a noise listening configuration for a mutual capacitancesense network 808 according to one embodiment. Sense network 808 caninclude TX electrodes (one highlighted as 880) arranged in one directionand RX electrodes (one highlighted as 882) arranged in anotherdirection. In the embodiment shown, sets of RX electrodes 882 (in thisembodiment, sets of two) can be connected to RX paths (RX0 to RX7) fornoise listening operations. TX electrodes 880 can be connected toground.

FIG. 8B shows a noise listening configuration for a mutual capacitancesense network 808 according to another embodiment. Sense network 808 canhave the structure shown in FIG. 8A. However, RX electrodes 882 and TXelectrodes 880 can be commonly connected to a same RX path. In theparticular embodiment shown, RX paths RX0 to RX3 can be connected to twoRX electrodes 882 and one TX electrode 880, while RX paths RX4 to RX7can be connected to two RX electrodes 882 and two TX electrodes 880.

In this way, RX and/or TX electrodes of a mutual capacitance sensenetwork can be connected to capacitance sensing inputs to listen fornoise while a TX signal is prevented from being applied to the network.

FIGS. 9A and 9B show listening operations according to embodiments.

FIG. 9A shows a listening operation 900-A having serial noise listeningoperations. Progression of time is shown by arrow “t”. A listeningoperation 900-A can begin with a listening scanning action 902. Such anaction can include acquiring capacitance values across multiple sensors(e.g., electrodes). In particular embodiments, such a step can includeestablishing connections to a mutual capacitance sense array like thatshown in FIG. 8A or 8B. Following a listening scanning 902, acquiredvalues can be subject to listening CMF 904. A listening CMF can includecommon mode filtering that can filter out noise common to all electrodesand thus help isolate local noise (e.g., external type noise). Filteredsense values can then be subject to a noise detection action 906. Suchan action can compare sensed capacitance levels to one or more limits todetermine a noise level. Following a noise detection action 906, alistening operation 900-A can repeat, performing another listeningscanning action 902.

FIG. 9B shows a listening operation 900-B having pipelined noiselistening operations. Progression of time is shown by arrow “t”. Alistening operation 900-B can begin with a listening scanning action902-1, which can acquire a first set of raw capacitance values.Following listening scanning operation 902-1, a next listening scanningoperation 902-2 can begin. However, while such second scanning action(902-2) is undertaken, the first set of raw data acquired with the firstscanning action 902-1 can be common mode filtered 904-1 and subject tonoise detection 906-1.

In this way, while raw data is gathered for noise listening onelectrodes, previously gathered raw data can be common mode filtered andchecked for noise events.

In some mutual capacitance embodiments, that drive TX electrodes with atransmit TX signal (i.e., excitation signal) while RX electrodes providesense signals via a mutual capacitance, in a listening scanning action(e.g., 902 and/or 902-1), capacitance can be sensed on RX electrodes,but without the TX electrodes being driven with a transmit signal.

FIG. 10 shows a noise listening operation 1000 according to oneembodiment in a flow diagram. An operation 1000 can include a scanninginitialization 1010. A scanning initialization can configure connectionsto a sense network to enable the sensing of noise across multiplechannels. Such an initialization can include changing sense networkconfigurations from a standard touch sensing configuration to a noiselistening configuration.

Once scanning initialization 1010 is complete, an operation 1000 can, inparallel, perform noise scanning 1012 and noise detection 1014. Noisescanning 1012 can include acquiring sense values from electrodes. Noisedetection 1014 can include detecting noise from previously acquiredsense values. Once noise scanning is complete (Yes from 1016), a noiselistening operation 1000 can restore a sense network to a normal state1018. A normal state can be that utilized for standard sensingoperations (e.g., touch sensing).

FIG. 11 shows a scanning initialization operation 1100 according to anembodiment. A scanning initialization operation 1100 can be oneparticular implementation of that shown as 1010 in FIG. 10. Scanninginitialization operation 1100 can be a scanning initialization operationfor a mutual capacitance sense network. An operation 1100 can includedisabling any circuits utilized in standard scanning operations thatcould interfere with noise detection (1120). In the embodiment shown, anaction 1120 can include turning off current digital-to-analog converters(iDACs) connected to a sense network. RX paths can be configured as highimpedance inputs (1122). RX paths can then be connected to inputchannels (1124). A signal acquisition time (e.g., scan time) can then beset that is suitable for the noise to be detected. In the embodiment ofFIG. 11, such an action can include setting a number of sub-conversions(1126) to a predetermined value. All active channels can then be turnedon (1128). Such an action can enable electrodes to be connected tocapacitance sensing circuits. A scan can then start (1130). Such anaction can acquire raw sense values to enable noise to be detected. Ascanning initialization operation 1100 can then end.

FIG. 12 shows a restore-to-normal operation 1232 according to anembodiment. A restore-to-normal operation 1232 can be one particularimplementation of that shown as 1018 in FIG. 10. Restore-to-normaloperation 1232 can include disconnecting all RX paths from inputchannels (1234). Such RX channels can then be configured for standardsensing operations (1236). A signal acquisition time (e.g., scan time)can then be returned to that utilized for standard sensing operations(1238). In the embodiment of FIG. 12, such an action can include settinga number of sub-conversions. An operation 1232 can include enablingpreviously disabled circuits utilized in standard scanning operations(1240). In the embodiment shown, an action 1240 can include turning oniDACs. A restore to normal operation 1232 can then end.

FIG. 13 shows a noise detection operation 1314 according to anembodiment. A noise detection operation 1314 can be one particularimplementation of that shown as 1014 in FIG. 10. A noise detectionoperation 1314 can include a CMF operation 1340. Such filtering canremove noise common to electrodes and thus can improve a signal from anylocal noise (i.e., external noise). Operation 1314 can then determine anoise value. In the particular embodiment shown determining a noisevalue can include finding maximum and minimum values from the CMFfiltered values (1342), and then determining the difference between suchvalues (1344).

A noise value can then be compared to a first threshold (1346). If anoise value is above a first threshold (Yes from 1346), a listeningtimeout value can be reset (1348) and a noise level can be set to afirst value (ON) (1350). If noise has been determined to above a firstthreshold, the noise can also be compared to a second threshold (1352).If a noise value is above a second threshold (Yes from 1352), a noiselevel can be set to a second value (Alarm) (1354). An operation can thenend 1366. If a noise value is below a second threshold (No from 1352),an operation can also end 1366.

If a noise value is not above a first threshold (No from 1346), a noisedetection operation 1314 can determine if a noise level should bereturned to a zero value (i.e., no noise). In the embodiment shown, if anoise level can be checked to see if it still indicates a high noisestate (i.e., ON or Alarm) (1356). If no elevated noise is indicated (Nofrom 1356) a timeout value can be reset (1348). If elevated noise isindicated (Yes from 1356) a timeout value can be incremented (1348). Thetimeout value can then be compared to a limit (1362). If a timeout valueexceeds a limit (Yes from 1362), the noise level can be returned to theno noise state (1350). If a timeout value does not exceed a limit (Nofrom 1362), an operation can end 1366.

FIG. 14 is a timing diagram showing a noise detection operationaccording to one embodiment. FIG. 14 includes a waveform NOISE DATA,showing noise sense values acquired by a noise listening operation.Projected onto the NOISE DATA waveform are two noise threshold levels(1^(st)_Threshold and 2^(nd)_Threshold).

FIG. 14 also includes a waveform NOISE LEVEL that shows noise levelsdetermined by a noise detection operation. NOISE LEVEL can indicatethree different noise levels. NoiseState=OFF can show noise values belowa first threshold (1^(st)_Threshold). NoiseState=ON can show noisevalues above the first threshold (1^(st)_Threshold). NoiseState=Alarmcan show noise values above a second threshold (2nd_Threshold).

Referring still to FIG. 14, at about time t0, noise values can exceed afirst threshold. As a result, a noise detection operation can set anoise level to ON. Eventually, noise levels time out, and at time t1,noise levels can return to an OFF state.

At about time t2, noise values can exceed a second threshold. As aresult, a noise detection operation can set a noise level to Alarm.Eventually, noise levels time out, and at time t3, noise levels canreturn to an OFF state.

Referring now to FIG. 15, a local noise filtering operation 1516according to an embodiment is shown in a flow diagram. A local noisefiltering operation 1516 can be performed on sense data in the eventlocal (i.e., not common mode) noise levels are determined to exceed acertain level. An operation 1516 can include inputting sense signals(1568). Such an action can include inputting raw count values generatedfrom an ADC connected to sense electrodes.

An operation 1516 can find a main signal (1570). Such an action canlocate a potential touch location. As will be recalled, local noise canpresent around touch locations. In one embodiment, a main signal cancorrespond to a sensor having a highest response (which would, in theabsence of noise, indicate a touch). An operation 1516 can then scalesignals from neighboring sensors to the corresponding main sensor signal(1572). Neighbor sensors can be sensors physically proximate to the mainsensor. In one embodiment, neighbor sensors can be sensor on opposingsides of a main sensor. A scaling operation can alter a sense value of aneighbor electrode based on how such an electrode varies from the mainwhen a valid touch event occurs.

In one very particular embodiment, scaling can be based on a mean valuewhen a touch is present for an electrode. Sense values for neighboringelectrodes can be scaled according to scaling factors as follows:k _(A)=(B _(Tmean) /A _(Tmean)), k _(C)=(B _(Tmean) /C _(Tmean))

where k_(A) is a scaling factor for a count value from an electrode Awhich is a neighbor of an electrode B, k_(C) is a scaling factor for acount value from an electrode C which is a neighbor of an electrode Bopposite electrode A, and A_(Tmean), B_(Tmean), and C_(Tmean) are meansense values derived from touches to such electrodes.

Following a scaling of neighbor sensors, a median filter can be appliedwith respect to the main signal (1574). Such an action can includeapplying a median filter to sense values for electrodes. In oneembodiment, a median filter can be applied to sensor signals from threeconsecutive time periods. A true touch event can provide an increasecount value that may be sustained over multiple time periods. Incontrast, local noise levels may vary in polarity over time. A medianfilter operation (e.g., 1574) can be a first type of non-linearfiltering that is performed.

An operation 1516 can also include an adaptive jitter filter (AJF)operation (1576). An AJF operation (e.g., 1576) can be anothernon-linear filter operation. One particular example of an AJF operationis described below in more detail.

Following an AJF operation (1576), a previous scaling operation (e.g.,1572) can be reversed. That is filtered sense values corresponding toneighbor sensors proximate a main sensor can be “unscaled” (1578). Aresulting set of sense values can then be output 1580.

FIGS. 16A and 16B show a determination of a main signal from electrodesaccording to an embodiment. FIGS. 16A and 16B show electrodes physicallyarranged into two groups, shown as slots 1684-0/1. A sense operation cansense capacitance values for different slots with different senseoperations. In one very particular embodiment, slots 1684-0/1 can be RXelectrodes coupled to a same TX electrode(s) by a mutual capacitance.

FIG. 16A shows a sense operation that determines electrode 1688 has ahighest response (count in this embodiment). Consequently, such anelectrode can be considered a “main” electrode. Electrodes 1686 adjacentto main electrode 1688 can be considered neighbor electrodes. Sensevalues corresponding to neighbor electrodes 1686 can be scaled withrespect to a sense value for main electrode.

FIG. 16B shows a sense operation in which main electrodes 1688 occur onends of adjacent slots 1684-0/1. In such an arrangement, a neighborelectrode 1686 for each main electrode can be an electrode in adifferent slot.

Referring now to FIGS. 17A and 17B, an AJF operation 1700 according toone embodiment is shown in flow diagram. An AJF can be one particularimplementation of that shown as 1576 in FIG. 15. An AJF operation 1700can perform filtering on a subset of electrodes based on averagedifference of such electrodes over time. FIGS. 17A and 17B are differentportions of a flow diagram, with connections between the two shown ascircled letters “a” and “b”.

Referring first to FIG. 17A, an AJF operation 1700 can include inputtingarrays of current signal values, and previously generated filteredsignal values (1702). In the embodiment shown, this can includeinputting values Msig⁻¹{0 . . . k} which can be previous filtered valuesgenerated by an AJF operation 1700 for an electrode set (e.g., a slot),values Sig⁻¹{0 . . . k} which can be previously input sense values forthe same electrode set (which in some embodiments can include scalingand/or median filtering), and values Sig{0 . . . k} which can be currentinput sense values for the same electrode set.

Various values can be initialized to zero, including a positivedisparity value sdp, a negative disparity value sdn, and iteration countvalues i and ir (1704). As will be understood from the discussion below,a positive disparity value sdp can represent the degree of correlationin a positive change from a previous sense value set and current a sensevalue set. A negative disparity value sdn can represent a samecorrelation, but in the other (i.e., opposite polarity) direction.

An operation 1700 can determine a difference between previous sensesignals and current sense signals (1706). In the embodiment shown, anarray Mdiff{0 . . . k} can be created that holds such values (referredto herein as difference values).

An operation 1700 can then generate positive and negative disparityvalues utilizing such difference values (1708). In the embodiment shown,such an action can include determining if a difference between aprevious sense value and its current level is positive, negative, orzero. A positive value will increase a positive disparity for theelectrode set. Similarly, a negative value will decrease a negativedisparity for the electrode set. In the embodiment shown, no differencein values (zero) can result in both positive and negative disparityvalues being increased.

Once disparity values have been generated, an operation can thencalculate an average sum of the differences between sense signal sets(i.e., current and previous set) (1710). A function “fix” can remove afractional part of a number (1711). Such an average value is shown asth_av in the embodiment of FIG. 17. If an average difference (th_av) isabove a threshold value (n from 1712), filtering can stop, and currentset of input values Sig{0 . . . k} can be saved as filter values for anext filter operation and can be output as filtered values (1718, 1722,1724). Such a threshold check can account from a multi-touch eventoccurring on the set of electrodes.

If an average difference (th_av) is below a threshold value (y from1712), disparity values can be compared against correlation limits(1714). If either (i.e., positive or negative) disparity value issufficiently small (n from 1714) filtering can once again end, with thecurrent set of input values Sig{0 . . . k} can be saved as filter valuesfor a next filter operation and output as filtered values (1718, 1722,1724).

If an average difference (th_av) is below a threshold value andcorrelation between sense signal sets is high (y from 1714) an averagedifference value th_av can be compared against a minimum value (in thiscase 0) (1716). If there is little difference between sense signal sets(y from 1716), a current signal sense value set and previous filteredsense value set can be averaged to create a current filtered sense valueset (1720). This set can be saved as filter values for a next filteroperation and output as filtered values (1718, 1722, 1724).

Referring now to FIG. 17B, when an average difference value (th_av) anddisparity values are within predetermined ranges, an operation 1700 cancall a weighting function 1726. A weighting function can increase sensevalues when a limited number of sense values in a set exceed a weighingthreshold. A weighting function according to one particular embodimentwill be described in more detail below. A weighting function can returna weighting value (delta_av) that can be used to weight sense values ina filtered set.

If a weighting function indicates no weighting (i.e., delta_av=0) (yfrom 1728), filtering can stop, and current set of input values Sig{0 .. . k} can be saved as filter values for a next filter operation andoutput as filtered values (1718, 1722, 1724).

If a weighting function provides a weighting value (i.e., delta_av≠0) (nfrom 1728), an operation can selectively weight current sense valuesbased on polarities of a difference value and the weighting value(delta_av). In particular, if a difference value for an electrode hasthe same polarity as the weighting value (n from 1730), the sense valuemay not be weighted.

However, if a difference value for an electrode has a different polaritythan the weighting value (y from 1730), a magnitude of difference valuecan be compared to the weighting value (1732). If a magnitude of adifference is less than that of a weighting value (n from 1732), amulti-pass value can be checked to determine if the present operation isan initial pass (1734). If it is an initial weighting pass (n from1734), an operation 1700 can continue to a next value of the set (1738).However, if it is a follow on weighting pass (y from 1734), a currentvalue can be set to a previous filtered value, and an operation 1700 cancontinue to a next value of the set (1738). If the magnitude of adifference between sense values is greater than that of a weightingvalue (y from 1732), the weighting value can be subtracted from thecurrent value (1740), and an operation 1700 can continue to a next valueof the set (1738).

When all sense values of a set have been examined for weighting, adifference set can be created from the weighted values (1742). Amulti-pass value can then be checked to determine if the presentoperation is a last pass (1744). If the operation is not a last pass (yfrom 1744), a weighting function can be called again with the updatedvalues. If the operation is a last pass (n from 1744), a current set offiltered values can be saved as filter values for a next operation andoutput as filtered values (1718, 1722, 1724).

Referring now to FIGS. 18A and 18B, a weighting function 1800 accordingto one embodiment is shown in flow diagram. A weighting function 1800can be one particular implementation of that shown as 1726 in FIG. 17. Aweighting function 1800 can weight sense values in a set of electrodeswhen limited numbers of electrodes in the set exceed a weight threshold.FIGS. 18A and 18B are different portions of a flow diagram, with aconnection between the two shown as circled letter “a”.

Referring first to FIG. 18A, a weighting function 1800 can includeinputting current filtered values Msig{0 . . . k} and difference valuesMdiff{0 . . . k} (1846). A function 1800 can then examine a filteredvalue for each electrode in a set to see if it exceeds a weightingthreshold (WTH). Each time a sense value exceeds a weighting threshold(WTH) a range value can be incremented (1848). Thus, a range value(range) can represent how many electrodes in a set exceed WTH.

Once a range value is established, a weighting value can be initialized(1849).

Each filtered value can be compared to a weighting threshold (1850).According to such a comparison, components of a resulting weightingvalue (delta_av) can be increased or decreased depending upon a rangevalue. In the embodiment shown, if a range value outside of some minimumand maximum value (in the embodiment shown, less than or greater thantwo), a weighting component can be a difference value for the filteredvalue (delta_av=delta_av+Mdiff[i]). However, if a range value is withina predetermined range (in this embodiment, is “2”), a weightingcomponent can be increased by multiplying by the difference value by aweighting factor (Nwg) (delta_av=delta_av+Nwg*Mdiff[i]).

Once all filtered values have been compared and components for theweighting value added up, an average of the values can be generated1852. In the embodiment shown, fractional portions of weighting valuescan then be removed (1853).

Referring now to FIG. 18B, if a weighting value is zero (y from 1854) aweighting function can end, and the weighting value (zero) can beprovided as an output weighting value (1856) (for use in the AJF). If aweighting value is positive, a maximum difference value (Max) from theset of difference values can be determined (1856). If a weighting value(delta_av) is greater than a maximum value (Max), the weighting valuecan be set to the maximum value (1858). In a similar fashion, if aweighting value is negative, a minimum value (Min) from the set ofdifference values can be determined (1860). If a weighting value(delta_av) is greater than a minimum value (Min), the weighting valuecan be set to the minimum value (1862).

A weighting value (delta_av) can then be bounded by a high limit valueDF_MAX and low limit value DF_MIN (1864). If a weighting value(delta_av) is greater than high limit, it can be set to the high limit.Similarly, if a weighting value (delta_av) is less than low limit, itcan be set to the low limit.

The resulting weighting value can then be provided as an outputweighting value (1856) (for use in the AJF).

It is understood that FIGS. 17A to 18B show an AJF and weightingfunction according to a very particular embodiment. Alternateembodiments can realize such operations, or equivalent operation, withother circuits and/or architectures.

FIG. 19 is a flow diagram showing another implementation of an AJFfilter and weighting function like that shown in FIGS. 17A to 18B. FIG.19 shows processing 1900 that includes a first section 1966 that cangenerate an average difference value (th_av), a positive disparity value(sdp), and negative disparity value (sdn), as described for FIG. 17A. Asecond section 1970 can generate a weighting value (delta_av) like thatdescribed for FIGS. 18A/B. A third section 1968 can generate filteroutput values as shown in FIG. 17B.

Referring now to FIG. 20, a median filter 2000 that can be included inthe embodiments is shown in a flow diagram. A median filter 2000 caninclude inputting a set of sense values from consecutive sample periods(i.e., a sample window) (2003). In the particular embodiment of FIG. 20,a sample window is three. A median of the three values can bedetermined, and then provided as an output value (2005).

Embodiments can be utilized in capacitance sense systems to reduce theadverse affects of noise local to a subset of all electrodes, such asthat arising from external noise source.

Embodiments can improve capacitance sensing of a device when it iscoupled to a charging device by filtering charger noise coupled to atouch object (e.g., finger).

The frequency hoping algorithm described above can be improved upon,possibly improving stability and performance even for noise below 3Vp-pwithin a range of 1-200 kHz square wave noise. The embodiments describedherein may be used to meet device requirements for charger noise. One ofthe improvements may include modifying a state machine to implement anadditional listening method independently checks actual raw countsvalues on each sensor to decide if a frequency change is needed. Othermethods in the embodiments described below may also be used to improvebaseline updates for all available configurations to maintain thebaselines up to date with possible changes in the device's environment.

Generally, the embodiments described above perform noise listenerscanning before normal scanning as illustrated in FIG. 1 and FIG. 2. Inorder to eliminate the listener's sensitivity to LCD common node noise,a common node filter is applied to the listener data. After filtering,the noise detector defines the noise level (based on thresholds andtimeout technique). If charger noise is not detected then the scanningand processing path is not charged, as illustrated in the standard scan104, 204. The normal scanning (e.g. with 8 sub-conversions) withpipeline filtering, CMF, baseline and difference calculation aretypically performed, as shown in 212 and 228 of FIG. 2. If theacceptable charger noise is detected (e.g., Rx channel is not saturatedand the system SNR is decreased but it is greater than 1-2) then thenormal scanning time is increased (e.g., twice as many conversions orthe like), as shown in the extended scan 114, 206. The pipelinefiltering (with CMF excluded), may perform median filtering 216-0,non-linear noise filtering 216-1, as well as baseline and differencecalculation 228, as illustrated in FIG. 2. If a non-acceptable noise isdetected (e.g., Rx channel is saturated and the system SNR is less than1), then a charger noise alarm flag is defined by the noise alarm 218and the system tries to solve the problem by charger noise scanning andprocessing path.

The idea of frequency hopping is to detect the noise which exceeds somethreshold and switch to different frequency which has the noise belowthreshold. If there's no one frequency in a list which meets noiserequirements than it will pick the most quiet one and operate on it. Thesystem may listen to the noise and turn on filtering in case ofexceeding some other acceptable noise threshold. The combination ofnoise listening and filtering with frequency hoping can use threedifferent thresholds: 1) a first noise threshold where the noise may befiltered with filters; 2) a second noise threshold where the noisecannot definitively be filtered by standard filters and may benefit froma frequency change; and 3) a third noise threshold where the noise isconsidered excessive noise and where the flag is sent to the host thatthe noise cannot be filtered.

FIG. 23 is a graph 2300 of detected noise 2301 and three noisethresholds 2302-2306 according to one embodiment. The detected noise2301 is shown as data values (also referred to as counts) in packetsbeing sent to the host. As shown in the FIG. 23, the detected noise 2301exceeds a first noise threshold 2302 at which charger armor feature isactivated. The charger armor feature refers to the different combinationof techniques described herein that identify, define, and filter thedetected noise on the device. The phrase “charger armor feature” is usedas a matter of convenience, but could include any one of the differentcombination of listening, detecting, and filtering techniques describedherein. The detected noise 2301 may also exceed a second noise threshold2304 at which charger armor filtering is activated and a frequencychange is needed. The combination of frequency hopping with the chargerarmor filtering may result in better noise suppression. The detectednoise 2301 may also exceed a third noise threshold 2306 at which thedetected noise 2301 is considered excessive noise. The host can ignorethe data (e.g., detected touches) during this condition.

FIG. 24 is a flow chart illustrating a method 2400 of noise suppressionaccording to one embodiment. The method 2400 may be performed byprocessing logic that may comprise hardware (circuitry, dedicated logic,etc.), software (such as is run on a general purpose computing system ora dedicated machine), firmware (embedded software), or any combinationthereof. In one embodiment, the controller 330, 430, 530 630 of FIGS. 3,4, 5 and 6 performs some of operations of method 2400. Alternatively,other components of the of the capacitance sensing system 300, 400, 500,and 678 of FIGS. 3, 4, 5, and 6 can perform some or all of theoperations of method 2400.

Referring to FIG. 24, the method 2400 begins with calibrating allavailable frequencies (block 2401), and initializing baselines for thosefrequencies (block 2402). Next, the processing logic scans the panel(block 2403) at a specified operating frequency. Next, processing logicdetermines if the charger armor feature of the device is enabled (block2404). If not, the processing logic proceeds to calculate a centroid(block 2460) as described below. However, if at block 2404 the chargerarmor feature is enabled, the processing logic listens to the noise(block 2405). The detected noise can be categorized into four levels: 1)“No Noise”—no noise is detected (e.g., noise is below the first noisethreshold 2302); 2) “Noise Level 1”—charger armor filter needed (noiseis above the first noise threshold 2302); 3) “Noise Level 3”—frequencychange is needed (noise is above the second noise threshold 2304); and4) “Noise Level 2”—excessive noise detected (noise is above the thirdnoise threshold 2306).

If the processing logic determines that the noise is in the “No Noise”level, in which the noise is less than the first noise threshold (block2410), the processing logic disables a median filter (block 2411). Ifthe processing logic determines that the noise is in the “Noise Level 1”(block 2420), the processing logic enables the median filter (block2421), and may perform a baseline update on the hopping frequencies(block 2422). If the processing logic determines that the noise is inthe “Noise Level 3” (block 2430), the processing logic enables themedian filter (block 2421), and determines whether all frequencies havebeen listened to (block 2432). If not all the frequencies have beenlistened to at block 2432, the processing logic selects a next availableconfiguration (block 2433). When all the frequencies have been listed toat block 2432, the processing logic selects the configuration with thelowest noise (block 2434). If the processing logic determines that thenoise is in the “Noise Level 2” (block 2440), the processing logic setsthe flag “Excessive Noise” (block 2441).

Next, the processing logic determines if the median filter is enabled(block 2450). If not, the processing logic sets the original number ofsub-conversions (block 2452), as described above in the normal scanning.However, if the median filter is enabled, the processing logic increasesthe number of sub-conversions (block 2451). For example, the number ofsub-conversions can be doubled as described above in the extendedscanning.

Next, the processing logic calculates a centroid (block 2560) of thedata that may or may not have been filtered. In yet a furtherembodiment, as depicted, the processing logic can determine if thedetected noise is excessive in “Noise Level 2” (block 2440), or thefrequency change is needed in “Noise Level 3” (block 2430) (block 2461).If not, the processing logic returns to scan the panel at block 2403. Ifyes, the processing logic assigns the previous number of touches to acurrent number of touches (block 2462). This may operate as a debouncefeature that may prevent reaction to glitches in the noise due to asingle sample having excess noise. Also, the debounce feature may beused to track the number of touches when transitioning to a newfrequency.

FIG. 25 is a flow chart illustrating a method of noise suppression withfrequency hoping and false touch filtering according to one embodiment.The method 2500 may be performed by processing logic that may comprisehardware (circuitry, dedicated logic, etc.), software (such as is run ona general purpose computing system or a dedicated machine), firmware(embedded software), or any combination thereof. In one embodiment, thecontroller 330, 430, 530 630 of FIGS. 3, 4, 5 and 6 performs some ofoperations of method 2500. Alternatively, other components of the of thecapacitance sensing system 300, 400, 500, and 678 of FIGS. 3, 4, 5, and6 can perform some or all of the operations of method 2500.

Referring to FIG. 25, the method 2500 begins with initializing hardware(block 2501) and initializing firmware (block 2502). Initializing thehardware may include setting up the circuitry used to scan theelectrodes of the sense network, such as the switching circuits, ADC,signal generators, etc. As part of initializing the firmware, theprocessing logic can assign global variables, initialize scanningsettings (block 2503) and initialize frequency hopping settings (block2504). Initializing the scanning settings at block 2503 may include, forexample, setting the number of scanning cycles (e.g., number ofsub-conversions) to be performed, which electrodes are to be scanned, ascan order, initialize any variables and thresholds associated withscanning, or the like. Initializing the frequency hopping settings atblock 2504 may include, for example, setting the available number offrequencies, variables and thresholds associated with the frequencyhoping algorithm, or the like. Next, the processing logic performs apre-scan routing (block 2505) in which the processing logic sets thescanning settings (block 2506), and executes the frequency hoppingalgorithm (block 2507). Also, as part of the pre-scanning routine, theprocessing logic can scan the electrodes to obtain baselines levels forthe electrodes. The baselines are measured when there is no touch on thedevice and are used to determine a change from the baseline (raw data)is above a touch threshold. The pre-scan routing may include othersystems operations as would be appreciated by one of ordinary skill inthe art having the benefit of this disclosure.

Next, the processing logic determines if the scanning is enabled (block2508). If not, the processing logic enables the scanning (block 2515),updates the registers (block 2516), and reports data to a host (block2517), returning to the pre-scan routine at block 2505. When thescanning is enabled at block 2508, the processing logic scans thesensors (block 2509) and processes the results (block 2510). As part ofprocessing the results, the processing logic can determine a differencebetween the raw counts and the baseline. The raw counts may be a digitalvalue that represents the capacitance measured on the electrodes. Also,as part of processing the results, the processing logic calculates thecentroid (block 2511). The centroid may determine a coordinate locationof the touch, such as the X/Y coordinates of the touch. This may bereported in terms of pixels, or in terms of a coordinate system mappingof the touch surface. The processing logic may also perform filteringwhen certain conditions apply, as described herein. In the depictedembodiment, the processing the results at block 2510 include performingfalse touch filtering (block 2520). Various embodiments of the falsetouch filtering performed at block 2520 are described below with respectto FIGS. 26-32.

In one embodiment, as part of processing the results, the processinglogic may also determine if the number of fingers proximate to the sensenetwork is greater than zero (block 2512). If so, the processing logicupdates the inactive baselines (block 2513) and returns to activeconfiguration (block 2514), such as returning to block 2515. Theinactive baseline updates may update the baseline values so that theyare adjusted for current conditions, such as the noise environment inwhich the device is currently operating. In one embodiment, a countermay be used for baseline updates. When the counter expires the updatescan be designated as inactive and can be updated when there are notouches. The counter value may be a programmable value based on thedesign specifications.

At block 2515, the processing logic can have an XY position (centroid)or a flag for excessive noise, and can determine if the scanning isenabled (block 2514), can update the registers (block 2516), and reportthe data to the host (block 2517). In one embodiment, the processinglogic sends an interrupt to the host to let a driver of the operatingsystem of the host know that there is new data. In the interim, theprocessing logic can return to the pre-scanning routine at block 2505 toperform another scan. In short, the method can check for noise, scan,calculate a position, and report to the host over and over while themethod is operating.

It should be noted that in one embodiment, the method 2500 is performedwithout blocks 2504, 2507, 2512, 2613, and 2514, as described above. Inanother embodiment, the method 2500 is performed with blocks 2504 and2507, but without blocks 2512-2514. In another embodiment, the method2500 is performed with blocks 2512-2514 and without blocks 2504 and2507. In another embodiment, the false touch filtering may be performedin other applications that do not perform frequency hopping performed atblock 2507 as would be appreciated by one of ordinary skill in the arthaving the benefit of this disclosure.

The flow chart of FIG. 25 shows how the frequency hopping algorithm andthe false touch filtering can be implemented in the architecture of acapacitive touch screen controller. In one embodiment, the capacitivetouch screen controller is the TrueTouch® capacitive touchscreencontrollers, such as the CY8CTMA3xx family of TrueTouch® Multi-TouchAll-Points touchscreen controllers, developed by Cypress SemiconductorCorporation of San Jose, Calif. The TrueTouch® capacitive touchscreencontrollers sensing technology to resolve touch locations of multiplefingers and a stylus on the touchscreens up to 5 inches, supportsleading operating systems, and is optimized for low-power multi-touchgesture and all-point touchscreen functionality. Alternatively, thefrequency hopping features may be implanted in other touchscreencontrollers, or other touch controllers of touch sensing devices. In oneembodiment, the frequency hopping features may be implanted with thecharger armor features for better noise suppression, such as fromchargers.

In one embodiment, the processing logic receives, from the electrodes,data representing capacitances of sense elements. Sense elements areintersections between the electrodes, such as one or more TX electrodesand one RX electrode. The processing logic processes the data toidentify activated sense elements from the sense elements of the sensenetworks. The processing logic filters the data to remove false touchevents based on a spatial relationship of activated sense elements. Thespatial relationship can be used to distinguish false touches and actualtouches. For example, the nature of false touches usually is that alocal maximum is a big spike caused by noise and most of the adjacentsense elements have no data (zero) or one or two sense elements have lowmagnitude values. The nature of actual touches is that a local maximumis a big spike caused by the touch object and adjacent sensors (morethan two) also have magnitude values (non-zero values), such asdescribed and illustrated with respect to FIG. 27.

In one embodiment, the processing logic identifies a local maximum fromamong the activated sense elements, identifies a set of adjacent senseelements that are adjacent to the local maximum, and distinguishesbetween an actual touch and a false touch based on the capacitances ofthe set of adjacent sense elements. In another embodiment, theprocessing logic processes the data by identifying a local maximum fromamong the activated sense elements and calculating a sum of magnitudevalues of the activated sense elements. The filtering done by theprocessing device in this embodiment includes comparing the sum againsta threshold value to distinguish between an actual touch and a falsetouch. In another embodiment, the processing logic identifying a localmaximum from among the activated sense elements, calculating a sum ofmagnitude values of the activated sense elements, and subtracting amagnitude value of the local maximum from the sum. Like above, theprocessing logic filters the data by comparing the sum against athreshold value to distinguish between an actual touch and a falsetouch.

In another embodiment, the processing logic identifies a local maximumfrom among the activated sense elements, identifies a set of adjacentsense elements that are adjacent to the local maximum, and calculating asum of magnitude values of the set of adjacent sense elements. In thisembodiment, the processing logic filters the data by comparing the sumagainst a threshold value to distinguish between an actual touch and afalse touch.

In one embodiment, the processing logic identifies the set of adjacentsense elements includes identifying a three-by-three square of senseelements around the local maximum. In yet a further embodiment, theprocessing logic determines whether the local maximum is located at acorner of the sense network and identifies three or more adjacent senseelements for the set when the local maximum is located at the corner ofthe sense network. In another embodiment, the processing logicdetermines whether the local maximum is located at an edge of the sensenetwork, and identifies five or more adjacent sense elements for the setwhen the local maximum is located at the edge of the sense network.

In another embodiment, the processing logic determines whether the localmaximum is located at a corner of the sense network. When the localmaximum is located at the corner of the sense network, the processinglogic identifies three adjacent sense elements for the set when thelocal maximum is located at the corner of the sense network andidentifies three or more virtual sense elements for the set when thelocal maximum is located at the corner of the sense network. Theprocessing logic mirrors the magnitude values of the three adjacentsense elements for the magnitude values of the three or more virtualsense elements. The processing logic calculates the sum by adding themagnitude values of the three adjacent sense elements and the magnitudevalues of the three or more virtual sense elements.

In another embodiment, the processing logic determines whether the localmaximum is located at an edge of the sense network. When the localmaximum is located at the edge of the sense network, the processinglogic identifies five adjacent sense elements for the set when the localmaximum is located at the edge of the sense network and identifies threeor more virtual sense elements for the set when the local maximum islocated at the edge of the sense network. The processing logic mirrorsthe magnitude values of the three adjacent sense elements for themagnitude values of the three or more virtual sense elements. Theprocessing logic calculates the sum by adding the magnitude values ofthe three adjacent sense elements and the magnitude values of the threeor more virtual sense elements.

In other embodiments, the processing logic identifies multiple localmaximums. For each of the local maximums, the processing logic repeatsthe operations described above to identify the adjacent sense elementsto each of the local maximums, calculates the sums of the magnitudevalues, and compares the sum against a threshold value to distinguishbetween an actual touch and a false touch.

The embodiments described herein may be used for false toucheselimination in a presence of charger noise in capacitive sensingsystems. For example, when the charger is plugged in to the device, thecharger may cause a lot of noise specifically along the receiving (RX)electrodes, causing false touches. The embodiments described herein ofthe false touch filtering analyze raw data on the surrounding sensorsnear a local maximum of the detected touch and determines whether thisis a real touch or a false touch. If the touch is determined as false itis removed from report to a host device. The embodiments describedherein may analyze input data in potentially noisy areas of the sensearray and may remove output data from reporting data that is treated asa noise after the analysis. The input data can be summed and compared toa threshold value that represents an actual touch. Alternatively, othertechniques may be used to distinguish between actual touches and falsetouches as would be appreciated by one of ordinary skill in the arthaving the benefit of this disclosure. Previous solutions use a commonmode signal and apply general filters to input data. However, somelocalized noise, such as charge noise, is a type of noise that isdistributed locally in touch areas. This type of noise, however, mayreduce effectiveness of the common mode filters. The previous filtersattempt to filter the input data to get clearer results of actualtouches. The embodiments described herein may reject output data byanalyzing the output data and not modifying the input data.

In one embodiment, the capacitive sensing device contains rows andcolumns of electrodes, such as in a capacitive sense array. A capacitivesense element can be made up of an intersection of a TX electrode (rowor column) and a RX electrode (column or row). The intersections aresometimes referred to as sensors. As a result of measuring mutualcapacitance in between each of TX and RX intersection, a controller mayreceive a matrix of measured raw counts representing the capacitances ofthe mutual capacitances of the intersections. The size of the matrix maybe for example N_Columns*M_Rows. When a conductive object, such as afinger or a stylus, is placed on the capacitive sense array theconductive object reduces the mutual capacitance between the senseelements underneath the conductive object and the controller registersthis change in capacitance. This change may be converted to a number andis stored in a resulting matrix. If this measured value exceeds adefined touch threshold, the controller reports a touch. However, theremay be different types of noise that are present in capacitive sensingsystems and may impact the measured raw counts, such as illustrated inFIG. 26.

FIG. 26 is a graph 2600 of a signal during a touch event 2601 with noise2602 according to one embodiment. The signal of FIG. 26 is shown as rawcounts over a number of samples. The signal increases in raw counts toindicate a touch event 2601. The touch event 2601 introduces the noise2602. One of the possible noise types for the noise 2602 may be chargernoise which is sort of common mode noise. Common mode noise is createdin chargers through the use of flyback transformers as part of theregulation circuit used to create both isolation and efficiency. Thecharger noise may manifest as the ground and power of a mobile devicethat fluctuates relative to ground. For example, a human finger may beat approximately earth ground potential but the charger isolates thedevice for safety. So the device, when plugged in to the externalimpulse charger, may moves relative to the finger's potential. When thetouch event happens, the finger may inject noise at the point of contactof the touch event, but with the signal phase and magnitude not alignedwith normal sensing. Since the coupled charge is not dependent on alocal TX signal, the coupled charge may inject charge for allintersections coupled to the associated touched RX and TX line(s)instead of just those intersections where the finger actually touches.

In one embodiment, the false touch filtering is implemented in a filtercircuit or as a filtering routine. The false touch filtering may bereferred to as Z-Coordinate Filter or RX Line Filter. The false touchfiltering may identify possible false touches on an activated RX senseelement (touched) and its neighboring sense elements. The false touchfiltering may eliminate those that are more likely false from reportingto the host device. As illustrated in FIG. 27, the nature of falsetouches usually is that the local maximum is a big spike caused by thenoise and surrounding sense elements or at least most of them are low inmagnitude. Real touch usually affects surrounding sense elements andthese surrounding sense elements have non-zero magnitudes. The falsetouch filtering may be used to reduce false touch events due to chargernoise, but the false touch filtering may be used for any types of noise,such as noise that has a spike in noise, or an abnormal distribution.

FIG. 27 illustrates a false touch 2710 and an actual touch 2720 oncommon receive (RX) sense elements according to one embodiment. Theactual touch 2720 has a local maximum S1 2721 and a set of adjacentsense elements 2722 that are activated by a touch. The false touch 2710has a local maximum S2 2711 and two sense elements 2712 that areactivated. Although the local maximum S2 2711 may have a high magnitudevalue, thus, triggering a possible touch, the other sense elements 2722are only two activated sense elements that are near the local maximum S22711. The spatial relationship of the local maximum S2 2711 suggest thatthe touch is a false touch. For example, the spatial relationshipsuggests that the touch is not evenly distributed among the localmaximum and adjacent sense elements. The sum of the magnitude values ofthe false touch 2710, when calculated, is much smaller than a sum of themagnitude values of the set of adjacent sense elements 2722 for theactual touch 2720. The sum of the set of adjacent sense elements 2722may be greater than a specified threshold, thus, indicating a touchevent; and the sum of the sense elements 2712 of the false touch 2710may be less than the specified threshold, thus, indicating a false touchevent.

In one embodiment, the false touch filtering calculate a sum of adjacentsense elements in a three-by-three square around a local maximum asillustrated in FIGS. 28 and 29. In one embodiment, the sum includes themagnitude value of the local maximum. In another embodiment, the sumexcludes the magnitude value of the local maximum. In some embodiments,the local maximum may be at an edge of the sense network or at a corner,as illustrated in FIG. 29. In these embodiments, the sum may include themagnitude values of the adjacent sensors, such as the remaining threesense elements when the local maximum is at a corner or the remainingfive sense elements when the local maximum is at an edge.

FIG. 28 illustrates a three-by-three square Z magnitude calculation ofan actual touch 2801, an actual touch 2811 at a corner 2810 of thesensor network, and an actual touch 2821 at an edge 2820 of the sensenetwork according to one embodiment. The actual touch 2801 isrepresented by a local maximum and a three-by-three square of senseelements 2802 disposed around the local maximum. The sum may becalculated using the magnitude values of the sense elements 2802.Alternatively, the sum may be calculated using the magnitude values ofthe sense elements 2802 and the local maximum. The magnitude value ofthe local maximum may or may not be subtracted from the sum beforecomparing the sum to the threshold value to distinguish between a touchand a false touch.

When the actual touch 2811 is at the corner 2810, the actual touch 2811is represented by the local maximum and the three remaining senseelements 2812. The boxes outside the corner 2810 are not sense elementsand do not have magnitude values. The sum may be calculated using themagnitude values of the three sense elements 2812. Alternatively, thesum may be calculated using the magnitude values of the three senseelements 2812 and the local maximum. Like above, the magnitude value ofthe local maximum may or may not be subtracted from the sum beforecomparing the sum to the threshold value to distinguish between a touchand a false touch.

When the actual touch 2821 is at the edge 2820, the actual touch 2821 isrepresented by the local maximum and the five remaining sense elements2822. The boxes outside the edge 2820 are not sense elements and do nothave magnitude values. The sum may be calculated using the magnitudevalues of the five sense elements 2822. Alternatively, the sum may becalculated using the magnitude values of the five sense elements 2822and the local maximum. Like above, the magnitude value of the localmaximum may or may not be subtracted from the sum before comparing thesum to the threshold value to distinguish between a touch and a falsetouch.

In some embodiments, the efficiency of the false touch filtering can beimproved by using one or more virtual sensors for the Z magnitudecalculation when local maximum is detected on the edge or in the corner,as illustrated in FIG. 29.

FIG. 29 illustrates a three-by-three square Z magnitude calculation ofan actual touch 2901, an actual touch 2911 at a corner 2910 of thesensor network, and an actual touch 2921 at an edge 2920 of the sensenetwork using virtual sensors according to one embodiment. The actualtouch 2901 is represented by a local maximum and a three-by-three squareof sense elements 2902 disposed around the local maximum. The sum may becalculated using the magnitude values of the sense elements 2902.Alternatively, the sum may be calculated using the magnitude values ofthe sense elements 2902 and the local maximum. The magnitude value ofthe local maximum may or may not be subtracted from the sum beforecomparing the sum to the threshold value to distinguish between a touchand a false touch.

When the actual touch 2911 is at the corner 2910, the actual touch 2811is represented by the local maximum, three remaining sense elements2912, and five virtual sensors 2913. Unlike the boxed outside the corner2810 of FIG. 28, the boxes outside the corner 2910 are virtual senseelements 2913. The virtual sense elements 2913 are not physicalelectrodes, but represent sense elements as if the local maximum werenot at the corner 2910. The virtual sense elements 2913 have mirroredmagnitude values of the three remaining sense elements 2912 through thelocal maximum. The sum may be calculated using the magnitude values ofthe three sense elements 2912 and the virtual sense elements 2913.Alternatively, the sum may be calculated using the magnitude values ofthe three sense elements 2912, the virtual sense elements 2913, and thelocal maximum. Like above, the magnitude value of the local maximum mayor may not be subtracted from the sum before comparing the sum to thethreshold value to distinguish between a touch and a false touch.

When the actual touch 2921 is at the edge 2920, the actual touch 2921 isrepresented by the local maximum, the five remaining sense elements2922, and three virtual sense elements 2923. Unlike the boxed outsidethe edge 2920 of FIG. 29, the boxes outside the edge 2920 are virtualsense elements 2923. The virtual sense elements 2923 are not physicalelectrodes, but represent sense elements as if the local maximum werenot at the edge 2920. The virtual sense elements 2923 have mirroredmagnitude values of three of the sense elements 2922 through the localmaximum. The sum may be calculated using the magnitude values of thefive sense elements 2922 and the virtual sense elements 2923.Alternatively, the sum may be calculated using the magnitude values ofthe five sense elements 2922, the virtual sense elements 2923, and thelocal maximum. Like above, the magnitude value of the local maximum mayor may not be subtracted from the sum before comparing the sum to thethreshold value to distinguish between a touch and a false touch.

In one embodiment, the non-physical, virtual sensors outside of a panelboundary contain magnitude values that are mirrored from the senseelements through the center sense element (identified as a localmaximum). For example, a touch at the edge has the virtual senseelements outside of the panel boundary and a touch at a corner has fivevirtual sense elements outside the panel boundary. The magnitude of thebottom right sense element of the sense elements 2912 may be mirrored tothe top right sense element of the virtual sense elements 2913. Themagnitude of the middle right sense element of the sense elements 2912may be mirrored to the middle left sense element of the virtual senseelements 2913. The magnitude of the middle bottom sense element of thesense elements 2912 may be mirrored to the middle top sense element ofthe virtual sense elements 2913. Similarly, the magnitude values of thesense elements 2922 may be mirrored to the virtual sense elements 2923when the touch 2921 is detected at the edge 2920. These mirrored valuesmay be used with the magnitude values of the active sense elements forthe Z magnitude even when the touch is detected at an edge or at acorner. It should be noted that the depicted embodiments illustrate atouch at a top right corner and a right side. In other embodiments, thefalse touch filtering can be used for touches at other corners and atother sides as would be appreciated by one of ordinary skill in the arthaving the benefit of this disclosure.

FIGS. 30A and 30B are flow charts illustrating a method 3000 of falsetouch filtering according to one embodiment. The method 3000 may beperformed by processing logic that may comprise hardware (circuitry,dedicated logic, etc.), software (such as is run on a general purposecomputing system or a dedicated machine), firmware (embedded software),or any combination thereof. In one embodiment, the controller 330, 430,530 630 of FIGS. 3, 4, 5 and 6 performs some of operations of method3000. Alternatively, other components of the of the capacitance sensingsystem 300, 400, 500, and 678 of FIGS. 3, 4, 5, and 6 can perform someor all of the operations of method 3000.

Referring to FIGS. 30A and 30B, the method 3000 begins with findinglocal maximums (block 3001). If the number of local maximums is greaterthan zero, as determined at block 3002, the processing logic identifiestouches (block 3003) and determines if the charger armor is enabled(block 3004). If at block 3004 the charger armor is enabled, theprocessing logic sets an index to zero (block 3005) and determines ifthe index is less than a number of touches (block 3006). If so, theprocessing logic calculates a sum of the three-by-three square of senseelements (block 3007), and finds a maximum value of the three-by-threesquare and saves the maximum value as a maximum index (block 3008).Next, at block 3009, the processing logic determines if a row locationof the touch is within two rows of the maximum index in a previous cycleand if a column location of the touch is within two columns of themaximum index in the previous cycle. Block 3009 may be used to determineif the current touch is the same touch as from a previous cycle. Inanother embodiment, a finger identifier may be used to determine if thecurrent touch is the same touch as from the previous cycle. If at block3009, the processing logic determines that the touch is a new touch (NewFinger Found=True) (block 3010), and increments the index (block 3026),returning to block 3006. Once the index is not less than the number oftouches at block 3006, the processing logic determines if the noiselevel is above “Noise Level 2” (block 3011).

If so, the processing logic can perform a debounce routine to ensure thetouch is a new touch. In particular, the processing logic determines ifan old touch count (number of touches before the new touch) is greaterthan zero (block 3012). If so, the processing logic determines if thenew touch is found and if the debounce count is less than two (block3013) If so, the processing logic increments the debounce count andholds the previous coordinate data (XY data). The processing logicdetermines if the debounce count is zero (block 3016). If not, theprocessing logic returns to block 3011. If at block 3012, the old touchcount is greater than zero, the processing logic sets the debounce countto zero (block 3015). Similarly, if at block 3013, the new touch is notfound, or the debounce is not less than two, the processing logic setsthe debounce count to zero at block 3015.

When the debounce count is zero at block 3016, the processing logic ifthe current touch count is not equal to the old touch count (block3017). If not equal, the processing logic returns to block 3011. Ifequal at block 3017, the processing logic sets an index to zero (block3018) and determines if the index is less than the touch count (block3019). As long as the index is less than the touch count, the processinglogic determines if a row location of the touch is within two rows ofthe maximum index in a previous cycle (block 3020). If not, theprocessing logic returns to block 3019 and increments the index (block3023). If the row location is within two rows, the processing logicdetermines if the sum of the three-by-three square of adjacent senseelements is less than ⅞ the maximum value of the three-by-three square.If not, the processing logic returns to block 3019 and increments theindex (block 3023). If the sum is less than ⅞ of the maximum value ofthe three-by-three square, the processing logic removes the indexedtouch from the report, identifying the touch as a false touch, andreturns to block 3019 and increments the index (block 3023).

When the index is not less than the touch count at block 3019, theprocessing logic saves the maximum row and the maximum column as thelocal maximum(es) of the touch(es) (block 3024), and reports thetouch(es) to the host device (block 3025).

Returning back to block 3002, if the local maximum is not greater thanzero, the processing logic sets the debounce count to zero (block 3027)and reports the touch(es) or no touches to the host device (block 3025).

In one embodiment, the false touch filtering described in FIGS. 30A-30Bmay be implemented in a device that tracks stationary or slowly movingtouch objects (e.g., fingers, stylus, or other conductive objects). Thisapproach checks for the previous location of the touch and not thecurrent touch's location, which may be disadvantage when the touch ismoving. The false touch filtering described in FIGS. 31A-31B uses adifferent approach that may provide various advantages over the approachin FIGS. 30A-30B. For example, the approach described below may workwith multiple touches on the touch surface (panel of electrodes) and maylocally identify potential noisy areas for each touch. Each of theseareas may have its own local maximum Z magnitude to be compared to theother touches on the touch surface. It should be noted that in theembodiments described below, the method removes the “at least twocolumns away from the previous signal” at block 3020. This may be doneto allowing false touch filtering when a larger touch might have twolocal maximums within two sense elements. Also, each touch position maybe compared not to previous touch location, but to a current senseelement with a maximum magnitude. This may significantly improveimmunity for moving touches, especially fast moving touches, on thetouch surface. This may need one additional loop for detecting themaximum magnitude first, as described below. In another embodiment, themethod described below may be executed prior to position calculation andcan save some extra time used by the position calculation of touchesthat are removed by the false touch filtering. In another embodiment, adebounce algorithm may be used for faster processing and the touches areanalyzed for possible bad touches even when the debounce is holding theprevious coordinate data (XY data). The method described below may bemore efficient than the method 3000, but may have a longer executiontime.

FIGS. 31A and 31B are flow chart illustrating a method 3100 of falsetouch filtering according to another embodiment. The method 3000 may beperformed by processing logic that may comprise hardware (circuitry,dedicated logic, etc.), software (such as is run on a general purposecomputing system or a dedicated machine), firmware (embedded software),or any combination thereof. In one embodiment, the controller 330, 430,530 630 of FIGS. 3, 4, 5 and 6 performs some of operations of method3100. Alternatively, other components of the of the capacitance sensingsystem 300, 400, 500, and 678 of FIGS. 3, 4, 5, and 6 can perform someor all of the operations of method 3100.

Referring to FIGS. 31A and 31B, the method 3100 begins with findinglocal maximums (block 3101). If the number of local maximums is greaterthan zero, as determined at block 3102, the processing logic identifiestouches (block 3103) and determines if the charger armor is enabled(block 3104). If at block 3104 the charger armor is enabled, theprocessing logic determines if the noise level is above “Noise Level 2”(block 3105). If yes, the processing logic determines if the touch countis not equal to the old touch count (block 3106). If yes at block 3106,the processing logic calculates a sum of the three-by-three square ofsense elements (block 3107) for each of the detected touches, sets anindex to zero (block 3108), and determines if the index is less than anumber of touches (block 3109). If yes, the processing logic sets asecond index to zero (block 3110), and determines if the second index isless than the number of touches (block 3112). If yes at block 3112, theprocessing logic determines if the second index is within 3 rows withinindexed touch (block 3113). If yes at block 3113, the processing logicsaves the index for the sense element that is greater than the sum ofthe magnitudes of the three-by-three square of sense elements (block3114), and returns to block 3112, incrementing the second index (block3115).

If not at any one of the blocks 3104, 3105, and 3106, the processinglogic calculates a touch position (block 3124), calculates a touch IDfor the touches (Block 3125), and reports the touches to the host (block3126). If at block 3112 the second index is less than the touch count,the processing logic sets the second index to zero (block 3116), andthen determines if the second index is less than the touch count (block3117). If yes, the processing logic determines if the second index iswithin 3 rows of the indexed touch (block 3118). If not, the processinglogic increments the second index (block 3122), returning to block 3117.If the second index is within 3 rows of the indexed touch, theprocessing logic determines if the sum of a three-by-three square of thesecond index is less than the ⅞ the sum of the three-by-three square ofthe first index (block 3119). If so, the processing logic removes thesecond index touch from the report (block 3121), and increments thesecond index (block 3122), returning to block 3117. If no at block 3119,the processing logic activates the debounce (sets debounce=true) (block3120), and increments the second index (block 3122), returning to block3117.

When the index is not less than the touch count at block 3109, theprocessing logic determines if the debounce feature is activated and thedebounce counter is less than two (block 3123). If yes, the processinglogic increments the debounce counter (block 3127), holds the previouscoordinate data (XY data) (block 3128), and reports the touches to thehost (block 3126). If at block 3123 the debounce feature is notactivated or the debounce feature is not less than two, the processinglogic calculates a touch position (block 3124), calculates a touch IDfor the touches (block 3125), and reports the touches to the host (block3126).

In another embodiment, the method is modified to remove false touchesfor one stationary finger. This may be achieved as described above withrespect to FIGS. 30A-30B, but may remove operations concerning thedebounce feature, as described below with respect to FIG. 32. It shouldbe noted that removing features from the false touch filtering mayprovide a less effective system, but may be a tradeoff for moresimplicity in the technique and for reducing execution time. It shouldbe noted that the methods described herein may be combined to achievedifferent benefits as would be appreciated by one of ordinary skill inthe art having the benefit of this disclosure.

FIG. 32 is a flow chart illustrating a method 3200 of false touchfiltering according to another embodiment. The method 3200 may beperformed by processing logic that may comprise hardware (circuitry,dedicated logic, etc.), software (such as is run on a general purposecomputing system or a dedicated machine), firmware (embedded software),or any combination thereof. In one embodiment, the controller 330, 430,530 630 of FIGS. 3, 4, 5 and 6 performs some of operations of method3200. Alternatively, other components of the of the capacitance sensingsystem 300, 400, 500, and 678 of FIGS. 3, 4, 5, and 6 can perform someor all of the operations of method 3200.

Referring to FIG. 32, the method 3200 begins with finding local maximums(block 3201). If the number of local maximums is greater than zero, asdetermined at block 3202, the processing logic identifies touches (block3203) and determines if the charger armor is enabled (block 3204). If atblock 3204 the charger armor is enabled, the processing logic calculatesa sum of the three-by-three square of sense elements (block 3205) foreach of the detected touches, and finds a maximum sum of three-by-threesquare and the magnitude value as the maximum index (block 3206). Next,the processing logic determines if the noise level is above “Noise Level2” (block 3207). If so, the processing logic removes all touches fromthe report that have a sum of the three-by-three square of adjacentsense elements that are less than ⅞ of the maximum sum of three-by-threesquare, and reports the touches to the host (block 3309). If no atblocks 3202, 3204, and 3207, the processing logic proceeds to block 3209to report the touches to the host.

In one embodiment, the methods 3000-3200 may be implemented in acapacitance sensing system, including a memory device, and a controllercoupled to the memory device. The controller may receive signals from asense network comprising multiple electrodes to detect a conductiveobject proximate to the multiple electrodes. In one embodiment, thecontroller includes a filter circuit to receive data representingcapacitance of the sense elements (intersections of the electrodes),process the data to identify activated sense elements from among thesense elements, and filter the data to remove false touch events basedon a spatial relationship of activated sense elements. In a furtherembodiment, the controller also includes a filter circuit configured tofilter output data to remove false touches caused by localized noiseevents. In another embodiment, the filter circuit is configured toidentify a local maximum from among the activated sense elements. Thefilter circuit may calculate a sum of magnitude values of the activatedsense elements, and subtract a magnitude value of the local maximum fromthe sum. The sum is compared against a threshold value to distinguishbetween an actual touch and a false touch. In another embodiment, thefilter circuit is configured to identify a set of adjacent senseelements that are adjacent to the local maximum, and calculate a sum ofmagnitude values of the set of adjacent sense elements. This sum doesnot include the magnitude value of the local maximum. Like above, thissum is compared against a threshold value to distinguish between anactual touch and a false touch. In one embodiment, the set of adjacentsense elements includes a three-by-three square of sense elements roundthe local maximum. In another embodiment, the set of adjacent senseelements may have the sense elements that are within one or two rows orcolumns of the local maximum. Alternatively, the adjacent sense elementsmay be identified differently as would be appreciated by one of ordinaryskill in the art having the benefit of this disclosure.

In another embodiment, the filter circuit is configured to determinewhether the local maximum is located at a corner of the sense network orat an edge of the sense network. In one embodiment, the filter circuitidentifies three adjacent sense elements for the set when the localmaximum is located at the corner of the sense network, and identifiesfive adjacent sense elements for the set when the local maximum islocated at the edge of the sense network. In another embodiment, thefilter circuit is further configured to mirror the magnitude values ofthe set for the magnitude values for a second set of virtual senseelements, respectively. In this embodiment, the sum is the magnitudevalues of the set of sense elements and the magnitude values of thesecond set of virtual sense elements.

In another embodiment, the capacitance sensing system includes a sensenetwork including electrodes that are disposed in a first set oftransmit (TX) electrodes and a second set of receive (RX) electrodes.The controller of the capacitance sensing system is configured tomeasure a mutual capacitance between at least one of the first set of TXelectrodes and an individual one of the second set of RX electrodes forone of the sense elements.

In another embodiment, a device includes a controller and a capacitancesensing array including multiple sense elements (e.g., intersections ofTX and RX electrodes). The controller includes a capacitance sensingcircuit coupled to the capacitance sensing array, and a filter circuitcoupled to the output of the capacitance sensing circuit. The controlleris configured to receive, from the capacitance sensing circuit, datarepresenting capacitances of the sense elements, process the data toidentify activated sense elements, and filter the data to remove falsetouch events based on a spatial relationship of activated senseelements. In one embodiment, the controller identifies a local maximumfrom among the activated sense elements, identifies a set of adjacentsense elements that are adjacent to the local maximum, and calculates asum of magnitude values of the set of adjacent sense elements. Thecontroller compares the calculated sum against a threshold value todistinguish between an actual touch and a false touch.

It should be noted that the embodiments of the false touch filtering aredescribed in connection with some charger armor filtering techniques andfrequency hopping techniques. However, in other embodiments, the falsetouch filtering may be implemented in other designs without the chargerarmor filtering techniques or the frequency hopping techniques.

The embodiments described herein may be used in various designs ofmutual capacitance sensing arrays of the capacitance sensing system, orin self-capacitance sensing arrays. In one embodiment, the capacitancesensing system detects multiple sense elements that are activated in thearray, and can analyze a signal pattern on the neighboring senseelements to separate noise from actual signal. The embodiments describedherein are not tied to a particular capacitive sensing solution and canbe used as well with other sensing solutions, including optical sensingsolutions, as would be appreciated by one of ordinary skill in the arthaving the benefit of this disclosure. The embodiments described hereincan use the false touch filtering to reject noise from the system,leaving only effective signals of touches. The false touch filtering maynote filter the input data, but the final result that is based on theinput data. As described herein, the false touch filtering may be usedwith other filtering techniques, such as charger armor filtering,frequency hopping, common mode filtering, median filtering, or the like.

Embodiments of the present invention, described herein, include variousoperations. These operations may be performed by hardware components,software, firmware, or a combination thereof. As used herein, the term“coupled to” may mean coupled directly or indirectly through one or moreintervening components. Any of the signals provided over various busesdescribed herein may be time multiplexed with other signals and providedover one or more common buses. Additionally, the interconnection betweencircuit components or blocks may be shown as buses or as single signallines. Each of the buses may alternatively be one or more single signallines and each of the single signal lines may alternatively be buses.

Certain embodiments may be implemented as a computer program productthat may include instructions stored on a computer-readable medium.These instructions may be used to program a general-purpose orspecial-purpose processor to perform the described operations. Acomputer-readable medium includes any mechanism for storing ortransmitting information in a form (e.g., software, processingapplication) readable by a machine (e.g., a computer). Thecomputer-readable storage medium may include, but is not limited to,magnetic storage medium (e.g., floppy diskette); optical storage medium(e.g., CD-ROM); magneto-optical storage medium; read-only memory (ROM);random-access memory (RAM); erasable programmable memory (e.g., EPROMand EEPROM); flash memory, or another type of medium suitable forstoring electronic instructions. The computer-readable transmissionmedium includes, but is not limited to, electrical, optical, acoustical,or other form of propagated signal (e.g., carrier waves, infraredsignals, digital signals, or the like), or another type of mediumsuitable for transmitting electronic instructions.

Additionally, some embodiments may be practiced in distributed computingenvironments where the computer-readable medium is stored on and/orexecuted by more than one computer system. In addition, the informationtransferred between computer systems may either be pulled or pushedacross the transmission medium connecting the computer systems.

Although the operations of the method(s) herein are shown and describedin a particular order, the order of the operations of each method may bealtered so that certain operations may be performed in an inverse orderor so that certain operation may be performed, at least in part,concurrently with other operations. In another embodiment, instructionsor sub-operations of distinct operations may be in an intermittentand/or alternating manner.

In the foregoing specification, the invention has been described withreference to specific exemplary embodiments thereof. It will, however,be evident that various modifications and changes may be made theretowithout departing from the broader spirit and scope of the invention asset forth in the appended claims. The specification and drawings are,accordingly, to be regarded in an illustrative sense rather than arestrictive sense.

1. A method, comprising: receiving, from a sense network comprising aplurality of electrodes, data representing capacitances of a pluralityof sense elements, wherein the plurality of sense elements areintersections between the plurality of electrodes; processing the datato identify activated sense elements from the plurality of senseelements, wherein the processing comprises: identifying a local maximumfrom among the activated sense elements; and identifying a set of senseelements that are adjacent to the local maximum; filtering the data toremove false touch events based on a spatial relationship of activatedsense elements, wherein the filtering comprises comparing a magnitudevalue of the local maximum against an aggregate value based on at leastthree of the set of sense elements to distinguish between an actualtouch and a false touch.
 2. The method of claim 1, wherein the filteringfurther comprises distinguishing between the actual touch and the falsetouch based on the capacitances of the set of sense elements.
 3. Themethod of claim 2, wherein the processing the data to identify theactivated sense elements further comprises calculating a sum ofmagnitude values of the activated sense elements, wherein the comparingcomprises comparing the sum against a threshold value to distinguishbetween the actual touch and the false touch.
 4. The method of claim 2,wherein the processing the data to identify the activated sense elementsfurther comprises: calculating a sum of magnitude values of theactivated sense elements; and subtracting the magnitude value of thelocal maximum from the sum, wherein the comparing comprises comparingthe sum against a threshold value to distinguish between the actualtouch and the false touch.
 5. The method of claim 2, wherein theprocessing the data to identify the activated sense elements furthercomprises calculating a sum of magnitude values of the set of senseelements, wherein comparing comprises comparing the sum against athreshold value to distinguish between the actual touch and the falsetouch.
 6. The method of claim 2, wherein the identifying the set ofsense elements comprises identifying a three-by-three square of senseelements around the local maximum.
 7. The method of claim 2, wherein theidentifying the set of sense elements comprises: determining whether thelocal maximum is located at a corner of the sense network; andidentifying at least three sense elements that are adjacent to the localmaximum for the set when the local maximum is located at the corner ofthe sense network.
 8. The method of claim 2, wherein the identifying theset of sense elements comprises: determining whether the local maximumis located at a corner of the sense network; identifying three senseelements that are adjacent to the local maximum for the set when thelocal maximum is located at the corner of the sense network; identifyingthree or more virtual sense elements for the set when the local maximumis located at the corner of the sense network; and mirroring themagnitude values of the three sense elements for the magnitude values ofthe three or more virtual sense elements, and wherein the calculatingthe sum comprises adding the magnitude values of the three senseelements and the magnitude values of the three or more virtual senseelements.
 9. The method of claim 2, wherein the identifying the set ofsense elements comprises: determining whether the local maximum islocated at an edge of the sense network; identifying five sense elementsthat are adjacent to the local maximum for the set when the localmaximum is located at the edge of the sense network; identifying threeor more virtual sense elements for the set when the local maximum islocated at the edge of the sense network; and mirroring the magnitudevalues of the five sense elements for the magnitude values of the threeor more virtual sense elements, and wherein the calculating the sumcomprises adding the magnitude values of the five sense elements and themagnitude values of the three or more virtual sense elements.
 10. Amethod comprising: receiving, from a sense network comprising aplurality of electrodes, data representing capacitances of a pluralityof sense elements, wherein the plurality of sense elements areintersections between the plurality of electrodes; processing the datato identify activated sense elements from the plurality of senseelements; and filtering the data to remove false touch events based on aspatial relationship of activated sense elements, wherein saidprocessing the data to identify the activated sense elements comprises:identifying a local maximum from among the activated sense elements;identifying a set of sense elements that are adjacent to the localmaximum, the identifying the set comprises: determining whether thelocal maximum is located at an edge of the sense network; andidentifying at least three sense elements that are adjacent to the localmaximum for the set when the local maximum is located at the edge of thesense network; and distinguishing between an actual touch and a falsetouch based on the capacitances of the set of sense elements.
 11. Acapacitance sensing system, comprising a controller coupled to thememory device, wherein the controller is configured to receive signalsfrom a sense network comprising a plurality of electrodes to detect aconductive object proximate to the plurality of electrodes, wherein thecontroller comprises a filter circuit, wherein the filter circuit isconfigured to: receive, from the sense network, data representingcapacitances of a plurality of sense elements, wherein the plurality ofsense elements are intersections between the plurality of electrodes;process the data to identify activated sense elements of the pluralityof sense elements; and filter the data to remove false touch eventsbased on a spatial relationship of activated sense elements, wherein thefilter circuit is further configured to: identify a local maximum fromamong the activated sense elements; identify a set of sense elementsthat are adjacent to the local maximum; and comparing a magnitude valueof the local maximum against an aggregate value based on at least threeof the set of sense elements to distinguish between an actual touch anda false touch.
 12. The capacitance sensing system of claim 11, whereinthe filter circuit is configured to: calculate a sum of magnitude valuesof the activated sense elements; subtract the magnitude value of thelocal maximum from the sum; and compare the sum against a thresholdvalue to distinguish between the actual touch and the false touch. 13.The capacitance sensing system of claim 11, wherein the filter circuitis configured to: identify a set of sense elements that are adjacent tothe local maximum; calculate a sum of magnitude values of the set ofsense elements; and compare the sum against a threshold value todistinguish between the actual touch and the false touch.
 14. Thecapacitance sensing system of claim 11, wherein the set of senseelements comprises a three-by-three square of sense elements around thelocal maximum.
 15. The capacitance sensing system of claim 13, whereinthe filter circuit is further configured to: determine whether the localmaximum is located at a corner of the sense network or at an edge of thesense network; identify three sense elements that are adjacent to thelocal maximum for the set when the local maximum is located at thecorner of the sense network; and identify five sense elements that areadjacent to the local maximum for the set when the local maximum islocated at the edge of the sense network.
 16. The capacitance sensingsystem of claim 15, wherein the filter circuit is further configured tomirror the magnitude values of the set for the magnitude values for asecond set of virtual sense elements, respectively, and wherein the sumis the magnitude values of the set of sense elements and the magnitudevalues of the second set of virtual sense elements.
 17. The capacitancesensing system of claim 11, further comprising the sense networkcomprising the plurality of electrodes, and wherein the plurality ofelectrodes comprises a first set of transmit (TX) electrodes and asecond set of receive (RX) electrodes, and wherein the controller isconfigured to measure a mutual capacitance between at least one of thefirst set of TX electrodes and an individual one of the second set of RXelectrodes for one of the plurality of sense elements.
 18. Thecapacitance sensing system of claim 11, further comprising a capacitancesensing array comprising a plurality of sense elements, the capacitancesensing array coupled to the controller.
 19. The capacitance sensingsystem of claim 18, wherein the controller is configured to: calculate asum of magnitude values of the set of sense elements; and comparing thesum against a threshold value to distinguish between the actual touchand the false touch.